code: def _load_pipeline(self):
      if self._pipeline_class is not None and self._pipeline is None:
          # if model has not been model has not been moved to device yet
          if not self._on_device:
              self.logger.info(f"Moving model to {self.device}")
              self.model.to(self.device)
              self._on_device = True
  
          self.logger.info(f"Initializing a pipeline")
          self._pipeline = self._pipeline_class(
              model=self.model,
              tokenizer=self.tokenizer,
              device=self.device,
          )
  
imports: import logging
  import os
  import tempfile
  from typing import Union
  from datasets import Dataset, DatasetDict, load_dataset, load_from_disk
  import torch
  from transformers import AutoConfig, AutoModel, AutoTokenizer, Seq2SeqTrainer, Seq2SeqTrainingArguments, Trainer, TrainingArguments
  from happytransformer.args import EvalArgs, TrainArgs
  from happytransformer.fine_tuning_util import EvalResult, FistStep, ZERO_2_SETTINGS, ZERO_3_SETTINGS
label_desc: Use image node_id 19 for calling the HappyTransformer obj's underlying member method code with example usage: obj._load_pipeline() without return types